A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms

Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing numbers of sequences. On the other hand, with the advent of a new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with an increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better quality, gives enormous advantages in terms of execution time and memory requirements. The proposed strategy allows one to decrease the time complexity of any known heuristic of O(N)^x$O{\left(N\right)}^x$ complexity by a factor of O(1/p)^x$O{(1/p)}^x$, where N$N$ is the number of sequences, x$x$ depends on the underlying heuristic approach, and p$p$ is the number of processing nodes. In particular, we propose a highly scalable algorithm, Sample-Align-D, for aligning biological sequences using Muscle system as the underlying heuristic. The proposed algorithm has been implemented on a cluster of workstations using the MPI library. Experimental results for different problem sizes are analyzed in terms of quality of alignment, execution time and speed-up.     

Dynamic hybrid automatic repeat request (DHARQ) for WiMAX – Mobile multihop relay using adaptive power control

Wireless multihop network is currently attracting much attention as a new wireless broadband access technology due to numerous benefits. This work proposes a power control scheme for WiMAX multihop relay system. In contrast to existing power control and optimization approaches, our proposed method uses an adaptive Channel Quality Measurement for a relay station to reduce interferences to other mobile station (MS) or relay station (RS) within the same cell and hence increase the number of hops per link and consequently maximize the spatial reuse. The proposed power control is applied to a new dynamic HARQ algorithm for adaptive channel quality enhancement. Simulation results have indicated that the proposed approach achieves superior BER/PER performance enhancement in comparison to previous related works.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

SimClus: an effective algorithm for clustering with a lower bound on similarity

Clustering algorithms generally accept a parameter k from the user, which determines the number of clusters sought. However, in many application domains, like document categorization, social network clustering, and frequent pattern summarization, the proper value of k is difficult to guess. An alternative clustering formulation that does not require k is to impose a lower bound on the similarity between an object and its corresponding cluster representative. Such a formulation chooses exactly one representative for every cluster and minimizes the representative count. It has many additional benefits. For instance, it supports overlapping clusters in a natural way. Moreover, for every cluster, it selects a representative object, which can be effectively used in summarization or semi-supervised classification task. In this work, we propose an algorithm, SimClus, for clustering with lower bound on similarity. It achieves a O(log n) approximation bound on the number of clusters, whereas for the best previous algorithm the bound can be as poor as O(n). Experiments on real and synthetic data sets show that our algorithm produces more than 40% fewer representative objects, yet offers the same or better clustering quality. We also propose a dynamic variant of the algorithm, which can be effectively used in an on-line setting.     

An optical solution to the 3-SAT problem using wavelength based selectors

In this paper, an optical wavelength-based method to solve a well-known NP-complete problem 3-SAT is provided. In the 3-SAT problem, a formula F in the form of conjunction of some clauses over Boolean variables is given and the question is to find if F is satisfiable or not. The provided method uses exponential number of different wavelengths in a light ray and considers each group of wavelengths as a possible value-assignment for the variables. It then uses optical devices to drop wavelengths not satisfying F from the light ray. At the end, remaining wavelengths indicate satisfiability of the formula. The method provides two ways to arrange the optical devices to select satisfying wavelengths for a given clause: simple clause selectors and combined clause selectors, both requiring exponential preprocessing time. After preprocessing phase, the provided method requires polynomial time and optical devices to solve each problem instance.     

Optimum weight design of fiber composite plates in flexure based on a two level strategy

This paper offers a method for weight optimization of multilayer fiber composite plates under the action of lateral loadings. The objective is to design a fiber composite plate of minimum thickness which can sustain multiple static loadings applied normal to its surface without exhibiting failure based on Tsai-Hill criterion in any of its layers. In this investigation, fiber orientation angles are treated as discrete variables, which can vary only by pre-assigned increments, while thicknesses of layers are treated as continuous variables. The optimization procedure is based on a two stage strategy; in the first of which only the fiber orientation angles for the layers are treated as variables, and in the second, only the layer thicknesses. A powerful criterion based on a load factor has been defined to find the best angle for a new layer in the first stage, and the method of center points has been used for thickness optimization in the second stage. After any angle and thickness optimization has been done, a new layer is added to the thickness and the procedure is repeated for other new layers. The end of the two stage procedure is signaled whenever the thickness of the new layer in the optimization process approaches zero; meaning that no new layers would improve the set of layers already found. In this way at the end of the optimization procedure the plate thickness would be made of a minimum number of layers whose fibers are optimally oriented, and whose thicknesses are minimal. A poor choice of layers in the stack produce near zero thickness for the respective layer, and are thus deleted from the set. A repeat process is performed after each cycle, to modify layer angles in order to compensate for errors due to approximations involved. The priorities exercised in the choice of new layers for inclusion in the set and exclusion of all the un-necessary ones, allow an optimal state of stacking sequence to be achieved. Several examples are given to demonstrate the operation of the algorithm.     

Effect of Iron sulfate as electrolyte additive on plasma electrolytic oxidation of aluminum alloy

This study has been carried out to investigate the incorporation of Iron(II) sulfate as an additive of electrolyte on formed AA1010 aluminum alloy, using plasma electrolytic oxidation method in silicate-based electrolytes containing Iron(II) sulfate. In order to fabricate nanocomposite coating, silicon nitride nanopowder was added to electrolyte. The effects of iron(II) sulfate additive on the voltage-time trend, microstructure, compositions, wear, and corrosion resistances of PEO coatings were investigated. In addition, current density and concentration of additive were studied as parameters that were effective on coating. Results showed that although FeSO₄ enters to the coating structure, but it does not develop a new phase. The corrosion and wear behavior of coated samples with FeSO₄ indicate an improvement as compared to those without additive.     

Facile one-pot synthesis of novel dicyanoanilines fused to tetrahydro-4H-thiopyran-4-one ring via Et3N/H2O catalyzed pseudo four-component reaction

A facile procedure is developed for one-pot synthesis of a new group of dicyanoanilines. Tetrahydro-4H-thiopyran-4-one, 1, undergoes a pseudo four-component reaction with various aldehydes bearing different groups and two equivalents of malononitrile in aqueous media in the presence of triethylamine (Et₃N). As a result, novel thiopyran-fused dicyanoanilines 4 are formed efficiently in the reaction mixtures in 90–97% yield within 9–12?h mixing at 40°C. Due to the polarity of the medium, products precipitate in the mixture spontaneously allowing for easy purification by recrystallization avoiding cumbersome chromatographic separations. Characterization of the products was performed by spectroscopic methods and, in one case, was further supported by X-ray crystallographic experiments.